Generating user-driven patient personas to support preventive health care activities of rural-living unattached patients.

Objective: This study created personas using quantitative segmentation and knowledge user enhancement to inform intervention and service design for rural patients to encourage preventive care uptake. Methods: This study comprised a cross-sectional survey of rural unattached patients and a co-design workshop for persona development. Cross-sectional survey data were analyzed for meaningful subgroups based on quartiles of preventive care completion. These quartiles informed "relevant user segments" grouped according to demographics (age, sex), length of unattachment, percentage of up-to-date preventive activities, health care visit frequency, preventive priorities, communication confidence with providers, and chronic health conditions, which were then used in the workshop to build the final personas. Results: 207 responses informed persona user segments, and five health care providers and 13 patients attended the workshop. The resulting four personas, included John (not up-to-date on preventive care activities), Terrance (few up-to-date preventive care activities), George (moderately up-to-date preventive care activities), and Anne (mostly up-to-date preventive care activities). Conclusion: Quantitative persona development with integrated knowledge user co-design/enhancement elevated and enriched final personas that achieved robust profiles for intervention design. Innovation: This project's use of a progressive methodology to build robust personas coupled with participant feedback on the co-design process offers a replicable approach for health researchers.

Nursing Informatics' Contribution to One Health.

OBJECTIVES: To summarise contemporary knowledge in nursing informatics related to education, practice, governance and research in advancing One Health. METHODS: This descriptive study combined a theoretical and an empirical approach. Published literature on recent advancements and areas of interest in nursing informatics was explored. In addition, empirical data from International Medical Informatics Association (IMIA) Nursing Informatics (NI) society reports were extracted and categorised into key areas regarding needs, established activities, issues under development and items not current. RESULTS: A total of 1,772 references were identified through bibliographic database searches. After screening and assessment for eligibility, 146 articles were included in the review. Three topics were identified for each key area: 1) education: "building basic nursing informatics competence", "interdisciplinary and interprofessional competence" and "supporting educators competence"; 2) practice: "digital nursing and patient care", "evidence for timely issues in practice" and "patient-centred safe care"; 3) governance: "information systems in healthcare", "standardised documentation in clinical context" and "concepts and interoperability", and 4) research: "informatics literacy and competence", "leadership and management", and "electronic documentation of care". 17 reports from society members were included. The data showed overlap with the literature, but also highlighted needs for further work, including more strategies, methods and competence in nursing informatics to support One Health. CONCLUSIONS: Considering the results of this study, from the literature nursing informatics would appear to have a significant contribution to make to One Health across settings. Future work is needed for international guidelines on roles and policies as well as knowledge sharing.

A cross-sectional study of the preventive health care activities of western Canadian rural-living patients unattached to primary care providers.

Prevention services, such as screening tests and vaccination, are underutilized, especially by rural populations and patients without a usual primary care provider. Little is known about the compounding impacts on preventive care of being unattached and living in a rural area and there has been no comprehensive exploration of this highly vulnerable population's prevention activities. The twofold purpose of this research was to examine rural unattached patients' prevention activity self-efficacy and completion and to explore their experiences accessing healthcare, including COVID-19 impacts. Two thirds of patients had been unattached for over one year, and over 20 % had been unattached for over 5 years; males experienced longer unattachment compared to females. Completion rates of prevention activities were relatively low, ranging from 5.9 % (alcohol screening) to 59 % (vision test). Most participants did not complete their prevention care activities in line with the Lifetime Prevention Schedule timeline: 65 % of participants had less than half of their activities up-to-date and only 6.7 % of participants were up to date on 75 % or more of their prevention activities. Participants with higher prevention self-efficacy scores were more likely to be up-to-date on associated prevention activities but the longer patients had been unattached, the fewer their up-to-date prevention activities. Patients expressed negative impacts of COVID-19 including walk-in clinics shutting down limiting access to care. These results suggest serious gaps in rural unattached patients' preventive care and highlight the need for support when they are without a usual primary care provider, which can be lengthy.

Artificial Intelligence -based technologies in nursing: A scoping literature review of the evidence.

BACKGROUND: Research on technologies based on artificial intelligence in healthcare has increased during the last decade, with applications showing great potential in assisting and improving care. However, introducing these technologies into nursing can raise concerns related to data bias in the context of training algorithms and potential implications for certain populations. Little evidence exists in the extant literature regarding the efficacious application of many artificial intelligence -based health technologies used in healthcare. OBJECTIVES: To synthesize currently available state-of the-art research in artificial intelligence -based technologies applied in nursing practice. DESIGN: Scoping review METHODS: PubMed, CINAHL, Web of Science and IEEE Xplore were searched for relevant articles with queries that combine names and terms related to nursing, artificial intelligence and machine learning methods. Included studies focused on developing or validating artificial intelligence -based technologies with a clear description of their impacts on nursing. We excluded non-experimental studies and research targeted at robotics, nursing management and technologies used in nursing research and education. RESULTS: A total of 7610 articles published between January 2010 and March 2021 were revealed, with 93 articles included in this review. Most studies explored the technology development (n = 55, 59.1%) and formation (testing) (n = 28, 30.1%) phases, followed by implementation (n = 9, 9.7%) and operational (n = 1, 1.1%) phases. The vast majority (73.1%) of studies provided evidence with a descriptive design (level VI) while only a small portion (4.3%) were randomised controlled trials (level II). The study aims, settings and methods were poorly described in the articles, and discussion of ethical considerations were lacking in 36.6% of studies. Additionally, one-third of papers (33.3%) were reported without the involvement of nurses. CONCLUSIONS: Contemporary research on applications of artificial intelligence -based technologies in nursing mainly cover the earlier stages of technology development, leaving scarce evidence of the impact of these technologies and implementation aspects into practice. The content of research reported is varied. Therefore, guidelines on research reporting and implementing artificial intelligence -based technologies in nursing are needed. Furthermore, integrating basic knowledge of artificial intelligence -related technologies and their applications in nursing education is imperative, and interventions to increase the inclusion of nurses throughout the technology research and development process is needed.